Se analizan las obras del siglo xviii de la colección del Fondo Antiguo Digital de Biblioteca de la Universidad de Sevilla para localizar las partes elaboradas con papeles decorados, con la finalidad ...de clasificarlos y describirlos según las propuestas de la literatura especializada. Para ello, se recuperan los registros incluidos en el repositorio de la colección digital, se visualizan las reproducciones digitales de las obras, se identifican las partes con papeles decorados y se describen siguiendo el modelo de clasificación de papeles decorados, previamente elaborado, inspirado en los trabajos del profesor Carpallo Bautista. El modelo está formado por seis técnicas y sus variantes. Dentro de los más de 6.700 ejemplares del siglo xviii de la colección del Fondo Antiguo Digital, 511 incluyen papeles decorados en sus encuadernaciones.
Digital technologies have been used to support mental health services for two decades, but the COVID-19 pandemic created a particular opportunity for greater utilization and more data-driven ...assessment of these digital technologies. This research aims to offer a scoping review of the characteristics and effectiveness of digital interventions that were employed to improve mental health in the real context of COVID-19 pandemic. A combination of search terms was applied for automatic search of publications in the relevant databases. The key features of included studies were extracted, including the intervention, participant, and study details. A total of 20 eligible studies were included in the final review, which were conducted across different geographic regions and among diverse cultural groups. Among them, fourteen studies mainly reported the impact of digital technologies on general population, while only one published study developed specific interventions for the isolated COVID-19 depressed patients in hospitals. Digital technologies identified in this review were mainly developed via web-based and mobile-based platforms, such as social networking and video conferencing applications. But less than half of them were aligned with theoretical approaches from standardized psychological treatments. Most of the studies have reported positive effects of digital technologies, either on improving general mental and emotional well-being or addressing specific conditions (e.g., depression, stress, and anxiety). This scoping review suggests that digital technologies hold promise in bridging the mental health-care gap during and after the COVID-19 pandemic, and calls for more rigorous studies to identify pertinent features that are likely to achieve more effective mental health outcomes.
Objective To build a comprehensive overview of the potential role of fish in improving nutrition with respect to certain micronutrient deficiencies in developing countries. Design A comprehensive ...literature review was completed. For this the electronic library databases ASFA, CABD and Scopus were systematically searched and relevant references cited in these sources were carefully analysed. The search terms used were 'fish', 'small fish species', 'micronutrients', 'food-based strategies', ‘fish consumption' and 'developing countries'. The quality of data on nutritional analyses was carefully reviewed and data that lacked proper information on methods, units and samples were excluded. Results The evidence collected confirmed the high levels of vitamin A, Fe and Zn in some of the small fish species in developing countries. These small fish are reported to be more affordable and accessible than the larger fish and other usual animal-source foods and vegetables. Evidence suggests that these locally available small fish have considerable potential as cost-effective food-based strategies to enhance micronutrient intakes or as a complementary food for undernourished children. However, the present review shows that only a few studies have been able to rigorously assess the impact of fish consumption on improved nutritional status in developing countries. Conclusions Further research is required in areas such as determination of fish consumption patterns of poor households, the nutritional value of local fish and other aquatic animals and the impact of fish intake on improved nutritional status in developing countries where undernutrition is a major public health problem.
Drugs that target the chief mediator of nuclear export, chromosome region maintenance 1 protein (CRM1) have potential as therapeutics for leukemia, but existing CRM1 inhibitors show variable ...potencies and a broad range of cytotoxic effects. Here, we report the structural analysis and antileukemic activity of a new generation of small-molecule inhibitors of CRM1. Designated selective inhibitors of nuclear export (SINE), these compounds were developed using molecular modeling to screen a small virtual library of compounds against the nuclear export signal (NES) groove of CRM1. The 2.2-Å crystal structure of the CRM1-Ran-RanBP1 complex bound to KPT-251, a representative molecule of this class of inhibitors, shows that the drug occupies part of the groove in CRM1 that is usually occupied by the NES, but penetrates much deeper into the groove and blocks CRM1-directed protein export. SINE inhibitors exhibit potent antileukemic activity, inducing apoptosis at nanomolar concentrations in a panel of 14 human acute myeloid leukemia (AML) cell lines representing different molecular subtypes of the disease. When administered orally to immunodeficient mice engrafted with human AML cells, KPT-251 had potent antileukemic activity with negligible toxicity to normal hematopoietic cells. Thus, KPT-SINE CRM1 antagonists represent a novel class of drugs that warrant further testing in AML patients.
The hepatic diseases are extremely common in clinical practice. The correct classification of liver fibrosis is extremely important, as it influences therapy and predicts disease outcomes. The ...purpose of this study is to compare the diagnostic performance of point-shear wave elastography (pSWE) and magnetic resonance elastography (MRE) in the hepatic fibrosis diagnostic. A meta-analysis was carried out based on articles published until October 2020. The articles are available at following databases: MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, Scientific Electronic Library Online, LILACS, Scopus, and CINAHL. Diagnostic performances were analyzed per METAVIR F2, using 3.5kPa as target fibrosis. Assessment of the methodological quality of the incorporated papers by the QUADAS-2 tool for pSWE and MRE. A total 2,153 studies articles were evaluated and 44 studies, comprising 6,081 patients with individual data, were included in the meta-analysis: 28 studies for pSWE and 16 studies for MRE. The pooled sensitivity and specificity were 0.86 (95%CI 0.80-0.90) and 0.88 (95%CI 0.85-0.91), respectively, for pSWE, compared with 0.94 (95%CI 0.89-0.97) and 0.95 (95%CI 0.89-0.98) respectively, for MRE. The pooled SROC curve for pSWE shows in the area under the curve (AUC) of 0.93 (95%CI 0.90-0.95), whereas the AUC for MRE was 0.98 (95%CI 0.96-0.99). The diagnostic odds ratio for pSWE and MRE were 41 (95%CI 24-72) and 293 (95%CI 86-1000), respectively. There was statistically significant heterogeneity for pSWE sensitivity (I² = 85.26, P<0.001) and specificity (I² = 89.46, P<0.001). The heterogeneity for MRE also was significant for sensitivity (I² = 73.28, P<0.001) and specificity (I² = 87.24, P<0.001). Therefore, both pSWE and MRE are suitable modalities for assessing liver fibrosis. In addition, MRE is a more accurate imaging technique than pSWE and can be used as alternative to invasive biopsy.
Purpose
The purpose of this paper is to determine the digital library usage patterns as a means of improving the system, as well as the user experience, to give appropriate recognition to the most ...popular dissertations’ authors and to measure the interest of non-academic users for dissertations defended at the University of Novi Sad (UNS).
Design/methodology/approach
A logging module of the digital library of theses and dissertations of University of Novi Sad (PHD UNS) application has been implemented. The module recorded the messages relating to the search queries and downloads over a three-year period from 2017–2019. These logs are analysed using the Elasticsearch, Logstash and Kibana (ELK) technology stack and the results are shown using graphs and tables.
Findings
The analysis determined the perfect time for weekly maintenance of the system, defined a recommendation for improving the system and revealed the most popular dissertations. A significant number of downloads and queries originated from citizens, i.e. users outside the academic community.
Practical implications
The conducted analysis defined recommendations for the system improvement which can be used by PHD UNS research and development (R&D) team and revealed the most popular dissertations which are used for the promotion of its authors through faculties’ websites.
Originality/value
To the best of the authors’ knowledge, this is the first study of ELK based log analysis of a Serbian language documents’ repository. Besides, the value of results for the PHD UNS R&D team and UNS rector team, the study proves that PhD digital library presents an important Open Science communication channel for presenting scientific results to the citizens.
Purpose
The purpose of this paper is to present the knowledge structure based on the articles published in
Library Hi Tech
. The research hotspots are expected to be revealed through the keyword ...co-occurrence and social network analysis.
Design/methodology/approach
Data sets based on publications from
Library Hi Tech
covering the time period from 2006 to 2017 were extracted from Web of Science and developed as testbeds for evaluation of the CiteSpace system. Highly cited keywords were analyzed by CiteSpace which supports visual exploration with knowledge discovery in bibliographic databases.
Findings
The findings suggested that the percentage of publications in the USA, Germany, China, and Canada are high. Further, the most popular keywords identified in
Library Hi Tech
were: “service,” “technology,” “digital library,” “university library,” and “academic library.” Finally, four research issues were identified based on the most-cited articles in
Library Hi Tech
.
Originality/value
While keyword plays an important role in scientific research, limited studies paid attention to the keyword analysis in librarian research. The contribution of this study is to systematically explore the knowledge structure constructed by the keywords in
Library Hi Tech
.
Self-diagnosis is the process of diagnosing or identifying a medical condition in oneself. Artificially intelligent digital platforms for self-diagnosis are becoming widely available and are used by ...the general public; however, little is known about the body of knowledge surrounding this technology.
The objectives of this scoping review were to (1) systematically map the extent and nature of the literature and topic areas pertaining to digital platforms that use computerized algorithms to provide users with a list of potential diagnoses and (2) identify key knowledge gaps.
The following databases were searched: PubMed (Medline), Scopus, Association for Computing Machinery Digital Library, Institute of Electrical and Electronics Engineers, Google Scholar, Open Grey, and ProQuest Dissertations and Theses. The search strategy was developed and refined with the assistance of a librarian and consisted of 3 main concepts: (1) self-diagnosis; (2) digital platforms; and (3) public or patients. The search generated 2536 articles from which 217 were duplicates. Following the Tricco et al 2018 checklist, 2 researchers screened the titles and abstracts (n=2316) and full texts (n=104), independently. A total of 19 articles were included for review, and data were retrieved following a data-charting form that was pretested by the research team.
The included articles were mainly conducted in the United States (n=10) or the United Kingdom (n=4). Among the articles, topic areas included accuracy or correspondence with a doctor's diagnosis (n=6), commentaries (n=2), regulation (n=3), sociological (n=2), user experience (n=2), theoretical (n=1), privacy and security (n=1), ethical (n=1), and design (n=1). Individuals who do not have access to health care and perceive to have a stigmatizing condition are more likely to use this technology. The accuracy of this technology varied substantially based on the disease examined and platform used. Women and those with higher education were more likely to choose the right diagnosis out of the potential list of diagnoses. Regulation of this technology is lacking in most parts of the world; however, they are currently under development.
There are prominent research gaps in the literature surrounding the use of artificially intelligent self-diagnosing digital platforms. Given the variety of digital platforms and the wide array of diseases they cover, measuring accuracy is cumbersome. More research is needed to understand the user experience and inform regulations.
The proliferation of mobile health (mHealth) applications is partly driven by the advancements in sensing and communication technologies, as well as the integration of artificial intelligence ...techniques. Data collected from mHealth applications, for example, on sensor devices carried by patients, can be mined and analyzed using artificial intelligence-based solutions to facilitate remote and (near) real-time decision-making in health care settings. However, such data often sit in data silos, and patients are often concerned about the privacy implications of sharing their raw data. Federated learning (FL) is a potential solution, as it allows multiple data owners to collaboratively train a machine learning model without requiring access to each other's raw data.
The goal of this scoping review is to gain an understanding of FL and its potential in dealing with sensitive and heterogeneous data in mHealth applications. Through this review, various stakeholders, such as health care providers, practitioners, and policy makers, can gain insight into the limitations and challenges associated with using FL in mHealth and make informed decisions when considering implementing FL-based solutions.
We conducted a scoping review following the guidelines of PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews). We searched 7 commonly used databases. The included studies were analyzed and summarized to identify the possible real-world applications and associated challenges of using FL in mHealth settings.
A total of 1095 articles were retrieved during the database search, and 26 articles that met the inclusion criteria were included in the review. The analysis of these articles revealed 2 main application areas for FL in mHealth, that is, remote monitoring and diagnostic and treatment support. More specifically, FL was found to be commonly used for monitoring self-care ability, health status, and disease progression, as well as in diagnosis and treatment support of diseases. The review also identified several challenges (eg, expensive communication, statistical heterogeneity, and system heterogeneity) and potential solutions (eg, compression schemes, model personalization, and active sampling).
This scoping review has highlighted the potential of FL as a privacy-preserving approach in mHealth applications and identified the technical limitations associated with its use. The challenges and opportunities outlined in this review can inform the research agenda for future studies in this field, to overcome these limitations and further advance the use of FL in mHealth.
The improvement of health indicators and life expectancy, especially in developed countries, has led to population growth and increased age-related diseases, including Alzheimer's disease (AD). Thus, ...the early detection of AD is valuable to stop its progress at an early stage.
This study systematically reviewed the current state of using deep learning methods on neuroimaging data for timely diagnose of AD. We reviewed different deep models, modalities, feature extraction strategies, and parameter initialization methods to find out which model or strategy could offer better performance.
Our search in eight different databases resulted in 736 studies, from which 74 studies were included to be reviewed for data analysis. Most studies have reported the normal control (NC)/AD classification and have shown desirable results. Although recent studies showed promising results of utilizing deep models on the NC/mild cognitive impairment (MCI) and NC/early MCI (eMCI), other classification groups should be taken into consideration and improved.
The results of our review indicate that the comparative analysis is challenging in this area due to the lack of a benchmark platform; however, convolutional neural network (CNN)-based models, especially in an ensemble way, seem to perform better than other deep models. The transfer learning approach also could efficiently improve the performance and time complexity. Further research on designing a benchmark platform to facilitate the comparative analysis is recommended.
Display omitted
•The early detection of AD is valuable to stop its progress.•The deep learning has been the researcher's interest due to its known capabilities.•NC vs. MCI and NC vs. eMCI classification results showed promising results of utilizing CNN-based frameworks.•The CNN-based models, mostly the ensemble of CNNs, could perform better than other models.•Designing a benchmark platform to facilitate the comparison among studies is recommended.
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